Requesting Dataset Access

After creating a DataShop account, you will have access to all public datasets. This allows you to explore the
functionality of DataShop.

To gain access to private datasets, visit the private
datasets page and click the Request Access button next to the name of the
project you would like to access. In the dialog that appears, enter a brief reason for why you
would like access. The request for access will be sent to the project's principal investigator
and data provider (if one exists).

The status of your request will be shown on the Access Requests
page under the heading My Requests for Access. Any projects for which you have
been given access will appear on the My Datasets page.

If you don't hear back regarding your access request, you can either click the Request Access
button again after 24 hours or contact the project's principal investigator outside of
DataShop. Similarly, if your request has been denied, you can click the Request Access button
to re-request access.

Sample Selector

Sample Selector is a tool for creating and editing
samples, or groups of data you compare across—they're
not "samples" in the statistical sense, but more like filters.

By default, a single sample exists: "All Data". With the Sample
Selector, you can create new samples to organize your data.

You can use samples to:

Compare across conditions

Narrow the scope of data analysis to a specific time range,
set of students, problem category, or unit of a curriculum (for example)

A sample is composed of one or more filters, specific
conditions that narrow down your sample.

Creating a sample

The general process for creating a sample is to:

Add a filter from the categories at the left to the composition
area at the right

Modify the filter to select the subset of data you're interested
in, saving it when done

View the sample preview table to see the effect of adding your filter,
making sure you don't have an empty set (ie, a filter or combination
of filters that exclude all transactions).

Name and describe the sample

Decide whether to share the sample with others who can view the
dataset

Save the sample

The effect of multiple filters

DataShop interprets each filter after the first as an additional
restriction on the data that is included in the sample. This is also known
as a logical "AND". You can see the results of multiple filters in the
sample preview as soon as all filters are "saved".